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Artificial intelligence for image analysis in oral squamous cell carcinoma: a review

Head and neck tumor differential diagnosis and prognosis have always been a challenge for oral pathologists due to their similarities and complexity. Artificial intelligence novel applications can function as an auxiliary tool for the objective interpretation of histomorphological digital slides. In...

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Main Author: Pereira-Prado, Vanesa (author)
Other Authors: Silveira, Felipe Martins (author), Sicco, Estefanía (author), Hochmann Valls, Jimena (author), Isiordia-Espinoza, Mario Alberto (author), González González, Rogelio (author), Pandiar, Deepak (author), Bologna-Molina, Ronell (author)
Format: article
Language:English
Published: 2023
Subjects:
Artificial intelligence
Deep learning
Digital image
Histopathological analysis
Machine learning
Oral squamous cell carcinoma
Online Access:https://hdl.handle.net/20.500.12008/42878
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Summary:Head and neck tumor differential diagnosis and prognosis have always been a challenge for oral pathologists due to their similarities and complexity. Artificial intelligence novel applications can function as an auxiliary tool for the objective interpretation of histomorphological digital slides. In this review, we present digital istopathological image analysis applications in oral squamous cell carcinoma. A literature search was performed in PubMed MEDLINE with the following keywords: “artificial intelligence” OR “deep learning” OR “machine learning” AND “oral squamous cell carcinoma”. Artificial intelligence has proven to be a helpful tool in histopathological image analysis of tumors and other lesions, even though it is necessary to continue researching in this area, mainly for clinical validation.

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